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News
July 24, 2026
'Physics Is What the World Is Literally Built On'
Physicist Nina Dzhanayeva, recipient of a Vladimir Potanin Foundation scholarship, focuses her research on nanophotonics. In this interview for the HSE Young Scientists project, she discusses nanowells, scientific intuition, and how physics can help in making frangipane cream puffs.
July 20, 2026
Scientists Create Open Dataset for Studying Concentration
A team of Russian researchers, including scientists from HSE University–St Petersburg, has developed the first open multimodal dataset containing recordings of brain activity, heart function, and video observations to help researchers understand what happens in the human brain during deep concentration. In the future, the dataset could accelerate the development of neural interfaces, rehabilitation technologies, and AI systems. The article has been published in Scientific Data.
July 20, 2026
‘Science Is Universal-It Knows No Borders
Fuad Aleskerov, Tenured Professor and Director of the International Centre of Decision Choice and Analysis at HSE University, together with his colleagues, has developed methods of network analysis in bibliometrics that have made it possible to identify patterns in the appearance and citation of publications in academic journals, as well as their influence on each other. When one or a number of studies are frequently cited by a wide range of journals, this is an indicator that the research is of high quality. By contrast, extensive cross-citation within a limited group of journals increases the likelihood of identifying a network of predatory publications.

 

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Аналитическое решение класса рекуррентных соотношений с аддитивной функцией степенного вида в целях анализа трудоёмкости рекурсивных алгоритмов

Автоматизация и современные технологии. 2011. № 03. С. 25–29.
Головешкин В., Пономарев А. В., Ulyanov M.

Analytical decision of the nonlinear recurrent correlation special class with exponential additive function is proposed. Researched recurrent correlation are typical for recursive algorithms laborious function, which have been developed by decomposition method and possess exponential laborious of the received decisions consolidation. Analytical decisions for recurrent correlation with arguments type floor and ceiling arising for researched class theoretical consideration are derived. Results make it possible to analytically receive of the recursive algorithms laborious functions which decompose of the determined task with exponential laborious of the decisions consolidation.

Priority areas: IT and mathematics business informatics
Language: Russian
Keywords: рекуррентные соотношенияrecursive algorithmslaboriousrecurrent correlationanalytical decisionрекурсивные алгоритмытрудоёмкостьаналитическое решение
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Added: June 22, 2012
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